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Homogeneous Charge Compression Ignition (HCCI) offers a significant potential to reduce CO2 as well as NOx and particulate emissions. However ensuring stable and efficient HCCI combustion in practical use is a challenge and requires sophisticated control concepts. In the present paper a closed loop control concept is investigated for this purpose. In order to optimize the closed loop control, adaptations with neural networks are introduced. Different sensor concepts for HCCI combustion control are presented and the benefit of the analysis of crankshaft movements is analyzed.

The new inline six-cylinder engine from BMW notoriously sets new standards on objective performance in power and torque and fuel consumption as well as on “Laufkultur” (engine refinement). It has been a general movement in recent years to design engines that not only perform, but also improve driver's feedback for performance on an emotional level. New is the degree of differentiation of this new engine through distinctive sound design for the whole bandwidth of vehicle categories ranging from a 5-Series luxury sedan to a Z3 roadster, or an X5 sports utility vehicle to a 3-Series compact car. For each BMW class, the intake and exhaust systems of the inline 6-cylinder engines have been tuned to highlight the subjective impression of performance according to the appropriate vehicle type.